This application discloses an image processing method and apparatus, and relates to the field of image processing technologies, to help optimize a color, a contrast, or a dynamic range of an image, so that an optimized image can be more objective, and robustness is improved. The method is applied to a terminal including a first camera and a second camera. The method includes: when an ISO of the first camera in a current photographing environment is greater than a first threshold, capturing a first image for a first scenario in the current photographing environment; capturing a second image for the first scenario; and optimizing the first image based on the second image to obtain a third image. An image style of the second image is better than that of the first image.

A method for determining a sensitivity distribution of magnetic resonance (MR) receiving coils may include obtaining a reference image of a region of interest (ROI) of a subject. Contrast information between at least two types of tissues of the ROI may be weakened in the reference image. The method may also include determining, based on the reference image, a preliminary radio frequency (RF) field map corresponding to the ROI. The method may also include obtaining a transmitting field map corresponding to the ROI. The method may also include determining, based on the preliminary RF field map and the transmitting map, a sensitivity distribution of MR receiving coils corresponding to the ROI.

A device may receive frames of a video capturing an analog meter with a dial and a needle, may process the frames to identify a center, a radius, and a perimeter of the dial, and may determine calibrated values for the dial. The device may apply a model to one of the frames to create a base mask, may apply thresholding for a dynamic HSV bounding value, to the base mask and the frames, to create masked frames, and may identify contours for the masked frames. The device may identify a quantity of points for each of the contours, may estimate angles of the needle of the analog meter based on the quantity of points, and may average the estimated angles to determine an averaged needle angle. The device may determine a needle direction based on the averaged needle angle and may calculate a meter reading.

One embodiment of an apparatus includes a reference position receiving unit configured to receive intermediate or end panorama reference position information input by a user, and a control unit configured to control an imaging device to begin generating a plurality of images to be used to generate a panoramic image based on the intermediate or end panorama reference position information input by the user after the reference position receiving unit receives the intermediate or end panorama reference position information.

The present disclosure may improve contrast and deep black by efficiently controlling local dimming in consideration of the ratio of a black image data and the non-uniformity in the area between blocks.

A computer-implemented method includes performing analysis to determine information associated with a high dynamic range (HDR) media content item. A standard dynamic range (SDR) version of the HDR media content item is derived using HDR metadata. The derivation including encoding the HDR media content item to SDR content and normalizing data of the SDR content. The HDR metadata and the SDR version of the HDR media content item are transmitted with embedding of the HDR metadata within a protocol with the SDR version to a storage service. The HDR metadata and the SDR version are caused to be received at a display device. The SDR version is converted to HDR per incremental portion with a dynamic range bounded based on the HDR metadata of the protocol.

The present disclosure provides a method and apparatus for converting an image format, an electronic device, a computer readable storage medium and a computer program product, relates to the field of artificial intelligence technology such as computer vision and deep learning, and can be applied to intelligent sensing ultra-definition scenarios. A specific implementation of the method includes: acquiring a to-be-converted standard dynamic range image; performing a convolution operation on the standard dynamic range image to obtain a local feature; performing a global average pooling operation on the standard dynamic range image to obtain a global feature; and converting the standard dynamic range image into a high dynamic range image according to the local feature and the global feature.

An information processing apparatus that functions as a non-limiting example image processing apparatus includes a processor. When an original image drawn with horizontally-long first pixels is to be drawn by square second pixels, the processor generates two intermediate image data in each of which the number of second pixels is 1.2 times the number of first pixels of the original image data, by generating a second area formed with six (6) second pixels arranged in a horizontal direction for each of first areas that are formed dividing the original image by every five (5) first pixels arranged in the horizontal direction, and outputs the two intermediate image data to a display control device. The display control device generates output image data by synthesizing the two intermediate image data, and outputs the generated output image data to a display. The output image data is generated in each of the second areas with colors that include colors of the second pixels at both ends, which are in agreement with colors of the first pixels at both ends in each corresponding first area and colors of the second pixels other than the both ends, each of which is generated based on colors of adjacent two first pixels in corresponding first area.

Disclosed are a pedestrian re-identification method and apparatus based on local feature attention. The method includes the following steps: S1: obtaining an original surveillance video image data set, and dividing the original surveillance video image data set into a training set and a test set in proportion; and S2: performing image enhancement on the original surveillance video image training set to obtain enhanced images, and converting the enhanced images into sequence data. The pedestrian re-identification technology based on local feature attention uses a multi-head attention mechanism neural network to capture, extract video image feature sequences and replace convolution kernels in a convolutional neural network, uses fully connected layers and an activation function to combine local pedestrian feature sequences into complete pedestrian feature sequences through a weight matrix, performs prediction on the obtained pedestrian feature sequences, outputs position coordinates of pedestrians in the images and selects pedestrians to realize pedestrian re-identification.

A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.